Emergency department visits by nursing home residents. A retrospective Italian study of administrative databases from 2015 to 2019.

BACKGROUND: Visits to Emergency Departments (ED) can be traumatic for Nursing Home (NH) residents. In Italy, the rate of ED visits by NH residents was recently calculated as 3.3%. The reduction of inappropriate ED visits represents a priority for National Healthcare Systems worldwide. Nevertheless, research on factors associated with ED visits is still under-studied in the Italian setting. This study has two main aims: (i) to describe the baseline characteristics of NH residents visiting ED at regional level; (ii) to assess the characteristics, trends, and factors associated with these visits. METHODS: A retrospective study of administrative data for five years was performed in the Piedmont Region. Data from 24,208 NH residents were analysed. Data were obtained by merging two ministerial databases of residential care and ED use. Sociodemographic and clinical characteristics of the residents, trends, and rates of ED visits were collected. A Generalized Linear Model (GLM) regression was used to evaluate the factors associated with ED visits. RESULTS: In 5 years, 12,672 residents made 24,609 ED visits. Aspecific symptoms (45%), dyspnea (17%) and trauma (16%) were the most frequent problems reported at ED. 51% of these visits were coded as non-critical, and 58% were discharged to the NH. The regression analysis showed an increased risk of ED visits for men (OR = 1.61, 95% CI 1.51-1.70) and for residents with a stay in NH longer than 400 days (OR = 2.19, 95% CI 2.08-2.31). CONCLUSIONS: Our study indicates that more than half of NH residents' ED visits could potentially be prevented by treating residents in NH. Investments in the creation of a structured and effective network within primary care services, promoting the use of health technology and palliative care approaches, could reduce ED visits and help clinicians manage residents on-site and remotely.

Trajectories and determinants of emergency department use among nursing home residents: a time series analysis (2012-2019).

BACKGROUND: Emergency department (ED) use among nursing home (NH) residents is an internationally-shared issue that is understudied in Italy. The long term care in Italy is part of the health system. This study aimed to assess trajectories of ED use among NH residents and determinants between demographic, health supply, clinical/functional factors. METHODS: A pooled, cross-sectional, time series analysis was performed in an Italian region in 2012/2019. The analysis measured the trend of ED user percentages associated with chronic conditions identified at NH admission. A GLM multivariate model was used to evaluate determinants of ED use. The variables collected were sex, age, assistance intensity, destination after discharge from NH, chronic conditions at NH admission, need for daily life assistance, degree of mobility, cognitive impairments, behavioural disturbances and were taken from two databases of the official Italian National Information System (FAR and C2 registries) that were combined to create a unique and anonymous code for each patient. RESULTS: A total of 37,311 residents were enrolled; 55.75% (20,800 residents) had at least one ED visit. The majority of the residents had cardiovascular (25.99%) or mental diseases (24.37%). In all pathologies, the percentage of ED users decreased and the decrease accelerated over time. These results were confirmed in the fixed effects regression model (coefficient for linear term (b = - 3.6177, p = 0, 95% CI = [- 5.124, - 2.1114]); coefficient for quadratic term = - 0.7691, p = 0.0046, 95% CI = [- 1.2953, - 0.2429]). Analysis showed an increased odds of ED visits involving males (OR = 1.27, 95% CI 1.24;1.30) and patients affected by urogenital diseases (OR = 1.16, 95% CI [1.031-1.314]). The lowest odds of ED visits were observed among subjects aged > 90 years (OR = 0.64, 95% CI [0.60-0.67]), who required assistance for their daily life activities (OR = 0.86; 95% CI = [0.82, 0.91]), or with serious cognitive disturbances (OR = 0.86; 95% CI = [0.84, 0.89]), immobile (OR = 0.93; 95% CI = [0.89, 0.96]), or without behavioural disturbances (OR = 0.92; 95% CI = [0.90, 0.94]). CONCLUSIONS: The percentage of ED users has decreased, through support from the Italian disciplinary long-term care system. The demographic, clinical/functional variables associated with ED visits in this study will be helpful to develop targeted and tailored interventions to avoid unnecessary ED use.

IL6-mediated HCoV-host interactome regulatory network and GO/Pathway enrichment analysis.

During these days of global emergency for the COVID-19 disease outbreak, there is an urgency to share reliable information able to help worldwide life scientists to get better insights and make sense of the large amount of data currently available. In this study we used the results presented in [1] to perform two different Systems Biology analyses on the HCoV-host interactome. In the first one, we reconstructed the interactome of the HCoV-host proteins, integrating it with highly reliable miRNA and drug interactions information. We then added the IL-6 gene, identified in recent publications [2] as heavily involved in the COVID-19 progression and, interestingly, we identified several interactions with the reconstructed interactome. In the second analysis, we performed a Gene Ontology and a Pathways enrichment analysis on the full set of the HCoV-host interactome proteins and on the ones belonging to a significantly dense cluster of interacting proteins identified in the first analysis. Results of the two analyses provide a compact but comprehensive glance on some of the current state-of-the-art regulations, GO, and pathways involved in the HCoV-host interactome, and that could support all scientists currently focusing on SARS-CoV-2 research.

Determinants of aggression against all health care workers in a large-sized university hospital.

BACKGROUND: The paper aims to describe the 3-year incidence (2015/17) of aggressive acts against all healthcare workers to identify risk factors associated to violence among a variety of demographic and professional determinants of assaulted, and risk factors related to the circumstances surrounding these events. METHODS: A retrospective observational study of all 10,970 health workers in a large-sized Italian university hospital was performed. The data, obtained from the "Aggression Reporting Form", which must be completed by assaulted workers within 72 h of aggression, were collected for the following domains: worker assaulted (sex, age class, years worked); profession (nurses, medical doctors, non-medical support staff, administrative staff, midwives); aggressive acts (activity type during aggressive acts, season, time and location of aggressive acts); and type of aggressive acts (verbal, non-verbal, consequences, aggressors). RESULTS: Three hundred sixty-four (3.3%) workers experienced almost one aggression. The majority of the assaulted workers were female (77.5%), had worked for 6/15 years and were Nurses (64.3%). The majority of aggressive acts occurred during assistance and patient care (38.2%), in the spring and during the afternoon/morning shifts and took place in locations where patients were present (47.3%). The most prevalent aggression type was verbal (76.9%). The patient was the most common aggressor (46.7%). 56% of those assaulted experienced interruptions in their work. Being female, being < 50 years of age, having worked for 6-15 years were significant risk factors for aggression. Midwives suffered the highest risk of experiencing aggression (RR = 12.95). The risk analysis showed that non-verbally aggressive acts were related to assistance and patient care with respect to activity type, to the presence of patients and during the spring and afternoon/evening. CONCLUSIONS: The findings suggest the parallel use of future qualitative studies to clarify the motivation behind aggression. These suggestions are needed for the implementation of additional adequate prevention strategies on either an organizational or a personal level.

Predictors and trajectories of ED visits among patients receiving palliative home care services: findings from a time series analysis (2013-2017).

BACKGROUND: Current policies recommend integrating home care and palliative care to enable patients to remain at home and avoid unnecessary hospital admission and emergency department (ED) visits. The Italian health care system had implemented integrated palliative home care (IHPC) services to guarantee a comprehensive, coordinated approach across different actors and to reduce potentially avoidable ED visits. This study aimed to analyze the trajectories of ED visit rates among patients receiving IHPC in the Italian healthcare system, as well as the association between socio-demographic, health supply, and clinical factors. METHODS: A pooled, cross-sectional, time series analysis was performed in a large Italian region in the period 2013-2017. Data were taken from two databases of the official Italian National Information System: Home Care Services and ED use. A clinical record is opened at the time a patient is enrolled in IHPC and closed after the last service is provided. Every such clinical record was considered as an IHPC event, and only ED visits that occurred during IHPC events were considered. RESULTS: The 20,611 patients enrolled in IHPC during the study period contributed 23,085 IHPC events; ≥1 ED visit occurred during 6046 of these events. Neoplasms accounted for 89% of IHPC events and for 91% of ED visits. Although there were different variations in ED visit rates during the study period, a slight decline was observed for all diseases, and this decline accelerated over time (b = - 0.18, p = 0.796, 95% confidence interval [CI] = - 1.59;1.22, b-squared = - 1.25, p < 0.001, 95% CI = -1.63;-0.86). There were no significant predictors among the socio-demographic factors (sex, age, presence of a non-family caregiver, cohabitant family members, distance from ED), health supply factors (proponent of IHPC) and clinical factors (prevalent disorder at IHPC entry, clinical symptoms). CONCLUSION: Our results show that use of ED continues after enrollment in IHPC, but the trend of this use declines over time. As no significant predictive factors were identified, no specific interventions can be recommended on which the avoidable ED visits depend.

In-silico cardiac aging regulatory model including microRNA post-transcriptional regulation.

In most developed countries, cardiovascular diseases are among the top causes of death and their development has been shown closely related to aging. In this context, because of their ability to pervasively influence gene networks, miRs have been found as possible key players in the development of cardiac pathologies, suggesting their potential role as therapeutic targets or diagnostic markers. Based on these assumptions, we hereby present a computational study that applies data fusion techniques coupled with network analysis theory to identify a regulatory model able to represent the relationship between key genes and miRs involved in cardiac senescence processes. The proposed model has been validated through an extensive literature analysis, which confirmed that 94% of the identified genes and miRs are related with cardiac senescence. Furthermore, two relevant genes of the model have been also validated by Western blot experiments on heart samples from young and old mice, confirming in vitro their ectopic expression in aged hearts. The pure computationally inferred model presented in the paper is therefore a good candidate to represent the relationship between key genes and miRs involved in cardiac senescence processes, and represents a reliable selection of genes and miRs for further studies, in order to elucidate and better detail their involvement in cardiac aging.

Nonretentive Bonded Ceramic Partial Crowns: Concept and Simplified Protocol for Long-lasting Dental Restorations.

PURPOSE: Adhesively luted partial ceramic crowns have been documented to be clinically more durable than direct composite restorations when minimally invasively restoring large defects (replacing two cusps or more) in posterior teeth. The clinical longevity of such restorations is largely determined by the tooth-preparation design, material selection and adhesive luting procedure. The most frequently recorded failure in medium- to long-term clinical trials is fracture of the restoration. The clinical protocol of adhesively luted partial ceramic crowns can be optimized by taking the etiology of these restoration fractures into account. In this article, a simplified nonretentive bonded ceramic partial crown concept is presented that aims to achieve an adhesively luted ceramic restoration - composite cement - residual tooth structure biomechanical unit that maximally resists functional aging. Therefore, the three primary components of the bonded restoration-cement-tooth complex must function in synergy. Methods, Results and Discussion: The clinical protocol starts with a tooth preparation designed to optimally absorb chewing stress. A stable, internally rounded and gently sloping tooth-preparation design with all outer margins inclined towards the tooth center assures a favorable and homogenous stress distribution with low cyclic fatigue subjected to the adhesive interface. This preparation form additionally enables the dental technician to fabricate a well-seating and -fitting ceramic restoration of uniform thickness. As restoration material, monolithic lithium-disilicate glass ceramic is sufficiently strong for the partial crown indication and preferred in order to decrease the fracture risk. Clinically essential for a long-lasting restoration is the optimal bond that can be obtained by combined micromechanical interlocking and chemical bonding of composite cement to hydrofluoric acid-etched and silanized glass ceramic. CONCLUSION: The clinical effectiveness of this nonretentive bonded ceramic partial crown concept is confirmed by the overall high success rate as well as the very low fracture and debonding rate, as was recorded in long-term clinical trials.

CyTRANSFINDER: a Cytoscape 3.3 plugin for three-component (TF, gene, miRNA) signal transduction pathway construction.

BACKGROUND: Biological research increasingly relies on network models to study complex phenomena. Signal Transduction Pathways are molecular circuits that model how cells receive, process, and respond to information from the environment providing snapshots of the overall cell dynamics. Most of the attempts to reconstruct signal transduction pathways are limited to single regulator networks including only genes/proteins. However, networks involving a single type of regulator and neglecting transcriptional and post-transcriptional regulations mediated by transcription factors and microRNAs, respectively, may not fully reveal the complex regulatory mechanisms of a cell. We observed a lack of computational instruments supporting explorative analysis on this type of three-component signal transduction pathways. RESULTS: We have developed CyTRANSFINDER, a new Cytoscape plugin able to infer three-component signal transduction pathways based on user defined regulatory patterns and including miRNAs, TFs and genes. Since CyTRANSFINDER has been designed to support exploratory analysis, it does not rely on expression data. To show the potential of the plugin we have applied it in a study of two miRNAs that are particularly relevant in human melanoma progression, miR-146a and miR-214. CONCLUSIONS: CyTRANSFINDER supports the reconstruction of small signal transduction pathways among groups of genes. Results obtained from its use in a real case study have been analyzed and validated through both literature data and preliminary wet-lab experiments, showing the potential of this tool when performing exploratory analysis.

An extended gene protein/products Boolean network model including post-transcriptional regulation.

BACKGROUND: Networks Biology allows the study of complex interactions between biological systems using formal, well structured, and computationally friendly models. Several different network models can be created, depending on the type of interactions that need to be investigated. Gene Regulatory Networks (GRN) are an effective model commonly used to study the complex regulatory mechanisms of a cell. Unfortunately, given their intrinsic complexity and non discrete nature, the computational study of realistic-sized complex GRNs requires some abstractions. Boolean Networks (BNs), for example, are a reliable model that can be used to represent networks where the possible state of a node is a boolean value (0 or 1). Despite this strong simplification, BNs have been used to study both structural and dynamic properties of real as well as randomly generated GRNs. RESULTS: In this paper we show how it is possible to include the post-transcriptional regulation mechanism (a key process mediated by small non-coding RNA molecules like the miRNAs) into the BN model of a GRN. The enhanced BN model is implemented in a software toolkit (EBNT) that allows to analyze boolean GRNs from both a structural and a dynamic point of view. The open-source toolkit is compatible with available visualization tools like Cytoscape and allows to run detailed analysis of the network topology as well as of its attractors, trajectories, and state-space. In the paper, a small GRN built around the mTOR gene is used to demonstrate the main capabilities of the toolkit. CONCLUSIONS: The extended model proposed in this paper opens new opportunities in the study of gene regulation. Several of the successful researches done with the support of BN to understand high-level characteristics of regulatory networks, can now be improved to better understand the role of post-transcriptional regulation for example as a network-wide noise-reduction or stabilization mechanisms.

A combined approach for genome wide protein function annotation/prediction.

BACKGROUND: Today large scale genome sequencing technologies are uncovering an increasing amount of new genes and proteins, which remain uncharacterized. Experimental procedures for protein function prediction are low throughput by nature and thus can't be used to keep up with the rate at which new proteins are discovered. On the other hand, proteins are the prominent stakeholders in almost all biological processes, and therefore the need to precisely know their functions for a better understanding of the underlying biological mechanism is inevitable. The challenge of annotating uncharacterized proteins in functional genomics and biology in general motivates the use of computational techniques well orchestrated to accurately predict their functions. METHODS: We propose a computational flow for the functional annotation of a protein able to assign the most probable functions to a protein by aggregating heterogeneous information. Considered information include: protein motifs, protein sequence similarity, and protein homology data gathered from interacting proteins, combined with data from highly similar non-interacting proteins (hereinafter called Similactors). Moreover, to increase the predictive power of our model we also compute and integrate term specific relationships among functional terms based on Gene Ontology (GO). RESULTS: We tested our method on Saccharomyces Cerevisiae and Homo sapiens species proteins. The aggregation of different structural and functional evidence with GO relationships outperforms, in terms of precision and accuracy of prediction than the other methods reported in literature. The predicted precision and accuracy is 100% for more than half of the input set for both species; overall, we obtained 85.38% precision and 81.95% accuracy for Homo sapiens and 79.73% precision and 80.06% accuracy for Saccharomyces Cerevisiae species proteins.

Determinants of COVID-19 vaccination worldwide: WORLDCOV, a retrospective observational study.

Introduction: The COVID-19 pandemic has resulted in numerous deaths, great suffering, and significant changes in people's lives worldwide. The introduction of the vaccines was a light in the darkness, but after 18 months, a great disparity in vaccination coverage between countries has been observed. As disparities in vaccination coverage have become a global public health issue, this study aimed to analyze several variables to identify possible determinants of COVID-19 vaccination. Methods: An ecological study was conducted using pooled secondary data sourced from institutional sites. A total of 205 countries and territories worldwide were included. A total of 16 variables from different fields were considered to establish possible determinants of COVID-19 vaccination: sociodemographic, cultural, infrastructural, economic and political variables, and health system performance indicators. The percentage of the population vaccinated with at least one dose and the total doses administered per 100 residents on 15 June 2022 were identified as indicators of vaccine coverage and outcomes. Raw and adjusted values for delivered vaccine doses in the multivariate GLM were determined using R. The tested hypothesis (i.e., variables as determinants of COVID-19 vaccination) was formulated before data collection. The study protocol was registered with the grant number NCT05471635. Results: GDP per capita [odds = 1.401 (1.299-1.511) CI 95%], access to electricity [odds = 1.625 (1.559-1.694) CI 95%], political stability, absence of violence/terrorism [odds = 1.334 (1.284-1.387) CI 95%], and civil liberties [odds = 0.888 (0.863-0.914) CI 95%] were strong determinants of COVID-19 vaccination. Several other variables displayed a statistically significant association with outcomes, although the associations were stronger for total doses administered per 100 residents. There was a substantial overlap between raw outcomes and their adjusted counterparts. Discussion: This pioneering study is the first to analyze the association between several different categories of indicators and COVID-19 vaccination coverage in a wide complex setting, identifying strong determinants of vaccination coverage. Political decision-makers should consider these findings when organizing mass vaccination campaigns in a pandemic context to reduce inequalities between nations and to achieve a common good from a public health perspective.

Paediatric hospitalizations over three waves of COVID-19 (February 2020 to May 2021) in Italy: determinants and rates.

Background: After a pneumonia outbreak in late 2019 in China, a new virus related to the Coronaviridae strain, called Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2), was identified as the pathogen of an emerging disease known as COronaVIrus Disease 19 (COVID-19). Preliminary evidence outlines a higher prevalence in adults and lower susceptibility in children. However, recent epidemiologic research highlighted that transmissibility and susceptibility among children and adolescents become higher due to new virus variants. Infections among youth arises with mainly respiratory and gastrointestinal symptoms and malaise. Nevertheless, critical illness affects new-borns and fragile children, requiring hospitalization and possibly intensive care support. Aim of this study was to examine the impact of COVID-19 pandemic on hospital admissions among children and adolescents aged 0 to 17 years over three waves of COVID-19 (from February 2020 to May 2021) in Piedmont, a large Italian region, and to investigate the possible determinants of hospitalizations. Methods: A meta-analysis for risk assessment was performed over three waves of COVID-19 (from February 2020 to May 2021). Data were extracted from the official Italian National Information System and ISTAT. Results: Overall, 442 paediatric patients were enrolled and admissions concerned mostly the age group 0-4 years (60.2%). Trends of hospitalization showed a slight increase of paediatric admissions already in March 2020 and a rise during second and third waves (November 2020, March 2021). Paediatric age-grouped hospitalizations (0-4; 12-17; 5-11) reproduced an analogous trend. The children and adolescent hospitalization rate appeared lower than overall population with a moderate slope of increase in comparison with population slope. Monthly hospitalization rate (per 100,000) of children and adolescents aged 0-17 years reproduced the increasing trend of hospitalization numbers. This trend was influenced, in particular, by the trend of hospitalization rates for children aged 0-4 years. The meta-analysis for risk assessment showed a decreased likelihood of rescue of hospitalizations in female, 5-11 and 12-17 age groups. Conversely, the meta-analysis showed a positive association between foreign nationality and hospitalizations. Conclusions: Our results show a comparable trend of paediatric hospital admissions for COVID-19 and of the entire population hospitalizations over three waves. COVID-19 hospital admissions increase with a bimodal age distribution and the most admissions are among patients aged ≤4 or 5-11 years. Significant predictive factors of hospitalization are identified.

The integration of clinical data in the assessment of multiple sclerosis - A review.

BACKGROUND AND OBJECTIVES: Multiple Sclerosis (MS) is a neurological disease associated with various and heterogeneous clinical characteristics. Given its complex nature and its unpredictable evolution over time, there isn't an established and exhaustive clinical protocol (or tool) for its diagnosis nor for monitoring its progression. Instead, different clinical exams and physical/psychological evaluations need to be taken into account. The Expanded Disability Status Scale (EDSS) is the most used clinical scale, but it suffers from several limitations. Developing computational solutions for the identification of bio-markers of disease progression that overcome the downsides of currently used scales is crucial and is gaining interest in current literature and research. METHODS: This Review focuses on the importance of approaching MS diagnosis and monitoring by investigating correlations between cognitive impairment and clinical data that refer to different MS domains. We review papers that integrate heterogeneous data and analyse them with statistical methods to understand their applicability into more advanced computational tools. Particular attention is paid to the impact that computational approaches can have on personalized-medicine. RESULTS: Personalized medicine for neuro-degenerative diseases is an unmet clinical need which can be addressed using computational approaches able to efficiently integrate heterogeneous clinical data extracted from both private and publicly available electronic health databases. CONCLUSIONS: Reliable and explainable Artificial Intelligence are computational approaches required to understand the complex and demonstrated interactions between MS manifestations as well as to provide reliable predictions on the disease evolution, representing a promising research field.

Impact of the Timing of Integrated Home Palliative Care Enrolment on Emergency Department Visits.

BACKGROUND: The association between timing of integrated home palliative care (IHPC) enrolment and emergency department (ED) visits is still under debate, and no studies investigated the effect of the timing of IHPC enrolment on ED visits, according to their level of emergency. This study aimed to investigate the impact of the timing of IHPC enrolment on different acuity ED visits. METHODS: A retrospective, pre-/post-intervention study was conducted from 2013 to 2019 in Italy. Analyses were stratified by IHPC duration (short ≤30 days; medium 31-90 days; long >90 days) and triage tags (white/green: low level of emergency visit; yellow/red: medium-to-high level). The impact of the timing of IHPC enrolment was evaluated in two ways: incidence rate ratios (IRRs) of ED visits were determined (1) before and after IHPC enrolment in each group and (2) post-IHPC among groups. RESULTS: A cohort of 17 983 patients was analysed. Patients enrolled early in the IHPC programme had a significantly lower incidence rate of ED visits than the pre-enrolment period (IRR=0.65). The incidence rates of white/green and yellow/red ED visits were significantly lower post-IHPC enrolment for patients enrolled early (IRR=0.63 and 0.67, respectively). All results were statistically significant (P<.001). Comparing the IHPC groups after enrolment versus the short group, medium and long IHPC groups had a significant reduction of ED visits (IRR=0.37, IRR=0.14 respectively), showing a relation between the timing of IHPC enrolment and the incidence of ED visits. A similar trend was observed after accounting for triage tags of ED visits. CONCLUSION: The timing of IHPC enrolment is related with a variation of the incidence of ED visits. Early IHPC enrolment is related to a high significant reduction of ED visits when compared to the 90-day pre-IHPC enrolment period and to late IHPC enrolment, accounting for both low-level and medium-to-high level emergency ED visits.

Impact of COVID-19 on emergency department visits among palliative home care recipients: a retrospective population-based cohort study in the Piedmont region, Italy.

Background: Integrated palliative home care (IHPC) is delivered to patients with progressive end-stage diseases. During the COVID-19 pandemic, IHPC needed to provide high-quality home care services for patients who were treated at home, with the goal of avoiding unnecessary care, hospital admissions, and emergency department (ED) visits. This study aimed to compare the ED visits of IHPC recipients in a large Italian region before and during the first two waves of the COVID-19 pandemic and to find sociodemographic or clinical characteristics associated with changes in ED visits during the first two waves of COVID-19 pandemic, compared with the period before. Methods: Administrative databases were used to identify sociodemographic and clinical variables of IHPC recipients admitted before and during the pandemic. The obtained data were balanced by applying a propensity score. The average number of ED visits before and during the pandemic was calculated by using the Welch's t test and stratified by all the variables. Results: Before and during the pandemic, 5155 and 3177 recipients were admitted to IHPC, respectively. These individuals were primarily affected by neoplasms. ED visits of IHPC recipients reduced from 1346 to 467 before and during the pandemic, respectively. A reduced mortality among IHCP patients who had at least one ED visit during the pandemic (8% during the pandemic versus 15% before the pandemic) was found. The average number of ED visits decreased during the pandemic [0.143, confidence interval (CI) = (0.128-0.158) versus 0.264, CI = (0.242-0.286) before the pandemic; p < 0.001] for all ages and IHPC duration classes. The presence of a formal caregiver led to a significant decrease in ED use. Medium and high emergency ED admissions showed no difference, whereas a decrease in low-level emergency ED admissions during the pandemic [1.27, CI = (1.194-1.345) versus 1.439, CI = (1.3-1.579) before the pandemic; p = 0.036] was found. Conclusion: ED visits among IHPC recipients were significantly decreased during the first two waves of the COVID-19 pandemic, especially in those individuals characterized by a low level of emergency. This did not result in an increase in mortality among IHPC recipients. These findings could inform the reorganization of home care services after the pandemic.

Screening and Identification of Putative Long Non-Coding RNA in Childhood Obesity: Evaluation of Their Transcriptional Levels.

Background and Methods: Long non-coding RNAs (LncRNAs) and microRNAs are involved in the pathogenesis of obesity, a multifactorial disease that is characterized by inflammation, cardiometabolic complications, and increased cancer risk among other co-morbidities. The up/down regulation of LncRNAs and microRNAs may play an important role in this condition to identify new diagnostic/prognostic markers. The aim of the study was to identify circulating inflammatory LncRNAs in obese adolescents (n = 54) and to evaluate whether their expression behaved differently compared to normal-weight adolescents (n = 26). To have a more complete insight, the expression of some circulating miRNAs that are linked to obesity (miR-33a, miR-223, miR-142, miR-199a, miR-181a, and miR-4454) were also analyzed. Results: LncRNAs and miRNAs were extracted simultaneously from plasma samples and amplified by Real-Time PCR. Among the 86 LncRNAs that were analyzed with custom pre-designed plates, only four (RP11-347E10.1, RP11-10K16.1, LINC00657, and SNHG12) were amplified in both normal-weight and obese adolescents and only SNHG12 showed significantly lower expression compared to the normal-weight adolescents (p = 0.026). Circulating miRNAs showed a tendency to increase in obese subjects, except for miR-181a expression. LncRNAs and miRNAs correlated with some clinical and metabolic parameters. Conclusions: Our results suggest the importance of these new biomarkers to better understand the molecular mechanisms of childhood obesity and its metabolic disorder.

Building gene expression profile classifiers with a simple and efficient rejection option in R.

BACKGROUND: The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. RESULTS: This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. CONCLUSIONS: This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional classifiers might not be available.

Nets-within-nets for modeling emergent patterns in ontogenetic processes.

Ontogenesis is the development of an organism from its earliest stage to maturity, including homeostasis maintenance throughout adulthood despite environmental perturbations. Almost all cells of a multicellular organism share the same genomic information. Nevertheless, phenotypic diversity and complex supra-cellular architectures emerge at every level, starting from tissues and organs. This is possible thanks to a robust and dynamic interplay of regulative mechanisms. To study ontogenesis, it is necessary to consider different levels of regulation, both genetic and epigenetic. Each cell undergoes a specific path across a landscape of possible regulative states affecting both its structure and its functions during development. This paper proposes using the Nets-Within-Nets formalism, which combines Petri Nets' simplicity with the capability to represent and simulate the interplay between different layers of regulation connected by non-trivial and context-dependent hierarchical relations. In particular, this work introduces a modeling strategy based on Nets-Within-Nets that can model several critical processes involved in ontogenesis. Moreover, it presents a case study focusing on the first phase of Vulval Precursor Cells specification in C.Elegans. The case study shows that the proposed model can simulate the emergent morphogenetic pattern corresponding to the observed developmental outcome of that phase, in both the physiological case and different mutations. The model presented in the results section is available online at https://github.com/sysbio-polito/NWN_CElegans_VPC_model/.

Effective Protocol for Daily High-quality Direct Posterior Composite Restorations. The Interdental Anatomy of the Class-2 Composite Restoration.

The importance of the interdental anatomy of a class-2 direct composite restoration is one of the most underestimated topics in direct posterior composite restorations. The proximal emergence profile of the restoration and the contact area should be designed to maximize arch continuity and to minimize food impaction. Other restorative criteria that must be fulfilled are marginal adaptation compatible with the dental and periodontal integrity, and geometry of the marginal ridge compatible with the mechanical integrity of the restoration under load. Shortcomings will result in masticatory discomfort, caries, periodontal problems and undesired movement of teeth. In vitro and in vivo studies showed that the use a contoured sectional metal matrix band with a separation clamp results in the tightest contact point. However, this matrix system also has shortcomings and does not give the expected result in all class-2 cavities. The variation in depth, width of the box, distance between the cervical cavity margin and the adjacent tooth requires customization of the interproximal space. In order to realize this, sectional matrix bands with several profiles of curvature, variation of wedges and separation clamps, and the use of teflon tape are required. In addition, dentists should follow a protocol allowing them to build a proximal composite surface that fulfills the required restorative criteria. Pre-wedging, space evaluation, interproximal clearance, correct selection, positioning and stabilization of the matrix band are important steps in this protocol.

Evaluation of the Strategies to Control COVID-19 Pandemic in Four European Countries.

On March 11, 2020, the World Health Organization (WHO) has officially declared the novel coronavirus outbreak a pandemic. The national governments deployed a series of severe control measures and a set of public health policies in order to stop the spread of COVID-19 pandemic. The aim of this study is to investigate the correlation between specific interventions and incident cases during the second wave in multiple and specific countries. The observational study was based on data from the Oxford COVID-19 Government Response Tracker (OxCGRT) source retrieved from October 1st, 2020 to January 10, 2021. Thirteen specific indicators related to measures adopted were considered. Four European countries were taken into account: Italy, German, Spain and UK. A vector autoregression (VAR) model and the Granger Causality test were performed to allow for an assessment of any possible effect induced by each control measure against the overall pandemic growth. Wald test was conducted to compute p-values. No correlation between the applied measures and incident cases in the four countries was shown by the Granger causality test. Only closings of workplaces (C2) and limits on private gatherings showed (C4) a significant correlation with incident cases in UK and restrictions on internal movement between cities/regions in Germany. The Granger causality also tested that C2 and C4 forecasted the decrease of incident cases after a time lag of 6-30 days in UK and Germany, respectively. Policy makers must analyze the context in which policies are set because of effectiveness of interventions can be influenced by local context and, especially, by socio-economic and demographic characteristics, and make a proper communication to support the resilience of the population capable of guaranteeing adherence to the interventions implemented.